How to analyze data before going for machine learning training?
Though there is no universal method which can be blindly used for all datasets, but here is what i usually do;


Fill missing values using interpolation or mean, if missing values
are less than 10-15 percent of number of rows else drop the column.
Encode categorical data using some kind of encoding, e.g. one hot, etc.
Then normalize/rescale columns.
Now look at the variance in each feature. Usually, features with more variance are more important.
Next, see the correlation among columns. If two columns are highly
correlated, you only need to keep only one.